Modeling and Multivariate Methods - SAS

Chapter 24 Visualizing, Optimizing, and Simulating Response Surfaces 557
The Profiler
The columns referenced in the formulas become the X columns (unless the column is also a Y).
Y, Prediction Formula are the response columns containing formulas.
Noise Factors are only used in special cases for modeling derivatives. Details are in “Noise Factors
(Robust Engineering)” on page 615.
Expand Intermediate Formulas tells JMP that if an ingredient column to a formula is a column that
itself has a formula, to substitute the inner formula, as long as it refers to other columns. To prevent an
ingredient column from expanding, use the Other column property with a name of "Expand Formula"
and a value of 0.
The Surface Plot platform is discussed in a separate chapter. The Surface Profiler is very similar to the
Surface Plot platform, except Surface Plot has more modes of operation. Neither the Surface Plot
platform nor the Surface Profiler have some of the capabilities common to other profilers.
The Profiler
The Profiler displays profile traces (see Figure 24.3) for each X variable. A profile trace is the predicted
response as one variable is changed while the others are held constant at the current values. The Profiler
recomputes the profiles and predicted responses (in real time) as you vary the value of an X variable.
• The vertical dotted line for each X variable shows its current value or current setting. If the variable is
nominal, the x-axis identifies categories. See “Interpreting the Profiles” on page 558, for more details.
For each X variable, the value above the factor name is its current value. You change the current value by
clicking in the graph or by dragging the dotted line where you want the new current value to be.
• The horizontal dotted line shows the current predicted value of each Y variable for the current values of
the X variables.
• The black lines within the plots show how the predicted value changes when you change the current
value of an individual X variable. In fitting platforms, the 95% confidence interval for the predicted
values is shown by a dotted blue curve surrounding the prediction trace (for continuous variables) or the
context of an error bar (for categorical variables).
The Profiler is a way of changing one variable at a time and looking at the effect on the predicted response.